Comparison of Performance of Feature Selection Methods

Abstract: Feature selection is a process of selecting the relevant subset of features among all the features in a dataset. The objective of the paper is to improve the performance level, understanding and reduce time complexity, which is also known as variable selection and attribute selection. In this paper, the best performance of feature selection methods has been examined using relief, fast clustering algorithm and ranked forward search algorithm. The results of performance of algorithms is compared and given in a graph.

Keywords: Feature Selection, Performance, Algorithms, Subset Features.